Recently, machine learning (ML), and more specifically deep learning (DL) techniques have shown promising performance in a range of medical image analysis tasks [1]}. In cardiac image analysis, most ML/DL techniques have considered the modalities of CMR and echocardiography in isolation. However, some works [2]}, [3]}, [4]} have shown that they can contain complementary information and so considering them in combination could have benefits in terms of performance. To date, these methods have been based upon traditional ML approaches such as multiview learning [2]}.
